CN105629731A - Low lift-drag ratio return device integrated guidance unloading method - Google Patents

Abstract

The invention discloses a low lift-drag ratio return device integrated guidance unloading method. The low lift-drag ratio return device integrated guidance unloading method is characterized in that a dimensionless three-freedom degree motion equation can be established according to a low lift-drag ratio aircraft reentry process kinetic model; on the basis of the comprehensive consideration of the reentry overload and landing precision, the predicted correction reentry guidance method can be combined with the standard orbital tracking method, and the integrated guidance strategy can be established; the unloading strategy can be analyzed, and the heeling angle parameter optimization problem can be described as the searching of sigma 0, and the target drop point deviation requirement can be satisfied by the specific speed of the last stage; and at last, the overload peak value can be defined as the fitness function, and with the help of the particle swarm optimization, the heeling angle of the overload peak value at the minimum value can be solved and used as the secondary initial reentry heeling angle of the actual flight. The low lift-drag ratio return device integrated guidance unloading method is advantageous in that the high overload problem during the low lift-drag ratio aircraft reentry process can be effectively solved by the optimization of the secondary reentry heeling angle, and the design and the optimization of the low lift-drag ratio aircraft can be facilitated, and the engineering realizability can be provided.

Description

A kind of low lift-drag ratio recoverable capsule integrated guidance discharging method

Technical field

The present invention relates to field of aerospace technology, particularly relate to a kind of low lift-drag ratio recoverable capsule integrated guidance discharging method.

Background technology

Reentering return task still commonly used low lift-drag ratio recoverable capsule in current aerospace engineering, and it is particularly critical to reenter the control problem of overload in task, premature beats is improper causes serious threat very likely to the life to pilot. Therefore to ensure the personal safety of pilot in manned space flight return task, it is ensured that aircraft security returns expected point of impact it is necessary to the overload in return course is applied control strategy, makes aircraft cross and is loaded in safety range. To returning premature beats problem first has to determine which kind of method of guidance of use. About Guidance and control method, existing part achievement in research, wherein has standard trajectory homing guidance both at home and abroad, and this method of guidance logic is simple, but it is more sensitive that aircraft is reentered initial value. The prediction correction reentry guidance method proposed in recent years, the method is real-time, but calculated performance proposes higher requirement. In the suppression to overload, specifically include that the discharging method based on matched asymptotic expansions, by adopting approximation method to be analyzed thus reducing numerical computations to overload; Saltatory overload suppressing method, is equivalent to aerodynamic lift Gravitational Disturbance and suppresses overload; Prediction load slows down strategy, changes load by initially reentering the adjustment of angle of heel. These methods alleviate the higher problem of overload to a certain extent, but still Shortcomings.

Summary of the invention

It is an object of the invention to overcome deficiency of the prior art, solve low lift-drag ratio aircraft and reenter higher problem of transshipping in process, and quickly realize the optimization of low lift-drag ratio aircraft saltatory reentry trajectory.

For this, the invention provides a kind of low lift-drag ratio recoverable capsule integrated guidance discharging method, the basis that saltatory reenters is designed Guidance Law, combine structure integrated guidance strategy by prediction correction guidance and standard trajectory homing guidance, and analyze unloading strategy on this basis, optimize secondary by particle swarm optimization algorithm and reenter angle of heel, definition overload peak value is fitness function, angle of heel when solving overload peak value minima initially reenters angle of heel as the secondary of practical flight, make guidance when meeting impact accuracy, realize the whole control reentering process overload and optimization, specifically include following steps:

Step 1, set up low lift-drag ratio aircraft and reenter the kinetic model of process;

The integrated guidance method design Guidance Law that step 2, employing prediction correction method of guidance and reference-trajectory guidance method combine:

According to the atmospheric density feature at differing heights layer, simultaneously take account of the precision to guidance and the requirement of calculated performance. Adopt a kind of integrated guidance method design Guidance Law predicting that correction method of guidance and reference-trajectory guidance method combine. Skip trajectory is divided into two stages, first reentry stage and secondary reentry stage. First reentry stage, highly about 120km, speed is about 11km/s, and this stage reentry velocity is relatively big, and the unstability of air is relatively big simultaneously, and correction reentry guidance method is to guarantee the precision of this phase guidance therefore to adopt robustness to predict preferably. First re-entry phase includes again descending branch, ascent stage and Kepler's section. Angle of heel is planned to the function of range-to-go by this stage, and on horizontal and vertical, voyage is carried out decoupling, makes the range-to-go orthodrome distance equal to current point to drop point of aircraft, and the differential equation of range-to-go is:

$\stackrel{\·}{s}=\frac{Vcos\mathrm{\γ}}{r}---\left(1\right)$

Wherein, r is the earth center distance to aircraft, and �� is flight path angle, and V is flight speed.

Terminal control condition:

��(t_f)=��_f, �� (t_f)=��_f, r (t_f)=r_f(2)

Angle of heel Parametric optimization problem can be described as: finds a ��₀, the specific speed in make it in the end stage disclosure satisfy that the offset landings requirement arriving target. For guaranteeing the OK range of angle of heel, and make planning continuous, adopt angle of heel linearization technique:

$\left|\mathrm{\σ}\right|={\mathrm{\σ}}_{2th}+({\mathrm{\σ}}_0-{\mathrm{\σ}}_{2th})\frac{s-s_{2th}}{s_0-s_{2th}}---\left(3\right)$

Wherein ��₀For initially reentering angle of heel, ��_2thAngle of heel, S is reentered for secondary₀For initial residual voyage, S_2thRange-to-go when reentering for secondary, is approximately 2000km, ��_2thTaking 70 ��, the methods such as therefore solving of �� can be converted into one-parameter and look for one's roots problem, available secant method solve, and the symbol of �� adopts horizontal logic.

Secondary re-entry phase is highly about 80km being 0.05g from overload. This stage characteristic be speed significantly lower than the first stage, less in the fluctuation of this stage atmospheric density. Therefore this stage adopts standard trajectory tracking, can reduce the aircraft requirement to calculated performance.

Step 3, definition fitness function:

The aircraft considered belongs to typical campanula halleri Halleri, and in flight course, aircraft normal g-load and axial acceleration are all likely to occur situation about surpassing the expectation, and therefore adopts the form of total overload

$n_a=\sqrt{L^2+D^2}---\left(4\right)$

Wherein, L and D respectively rises/drag acceleration, defines as follows:

D=�� (V_sV)²S_refC_D/(2m)(5)

L=�� (V_sV)²S_refC_L/(2m)(6)

Wherein, S_retFor aircraft with reference to surface area windward. For aircraft with reference to surface area, C windward_DAnd C_LRespectively resistance and lift coefficient, m is vehicle mass, and �� is atmospheric density, and the scale factor of speed V isR₀For earth radius, g₀=9.81m/s.

Formula (5) and (6) are substituted into (4) can obtain:

$n_a=\mathrm{\ρ}{\left(V_{s}V\right)}^2{S}_{ref}\sqrt{C_L^2+C_D^2}/\left(2m\right)\∝{\mathrm{\ρV}}^2---\left(7\right)$

Having significant change in first re-entry phase and secondary re-entry phase aircraft speed, first re-entry phase speed is relatively big, but atmospheric density is relatively small; And secondary re-entry phase speed reduces to some extent, but atmospheric density is relatively large, and therefore, in ablated configuration process, overload is it is possible that two minor peaks, defines following fitness function:

Fitnessfunction=max [n_a(��_2th)](8)

Step 4, to described fitness function global optimization, by optimize ask for total overload values minimum time angle of heel, and this angle of heel is initially reentered angle of heel as the secondary of practical flight, wherein secondary reenters initial angle of heel ��₀In (0 ��, 90 ��) interval value.

The optimization of distribution and the angle of heel of overload has much relations, unsuitable angle of heel to there is a possibility that aircraft bears unnecessary overload, brings the selection of angle of heel that security threat, secondary reenter to be transship the key optimized in guidance to occupant. Experimental analysis is it can be seen that secondary reenters initial angle of heel ��₀Time too low, it is possible to can cause that aircraft in the end stage voyage regulating power is not enough, destroy aircraft lands precision.

Step 5, according to optimum results export corresponding reentry trajectory.

Above-mentioned steps 1 sets up low lift-drag ratio aircraft, and to reenter the kinetic model of process be dimensionless three-degree-of-freedom motion equation, specific as follows:

$\stackrel{\·}{r}=Vsin\mathrm{\γ}---\left(9\right)$

$\stackrel{\·}{\mathrm{\θ}}=\frac{Vcos\mathrm{\γ}sin\mathrm{\ψ}}{rcos\mathrm{\φ}}---\left(10\right)$

$\stackrel{\·}{\mathrm{\φ}}=\frac{V\cos ycos\mathrm{\ψ}}{r}---\left(11\right)$

$\stackrel{\·}{V}=-D-\left(\frac{sin\mathrm{\γ}}{r^2}\right)+{\mathrm{\Ω}}^{2}rcos\mathrm{\φ}\sin \mathrm{\γ}cos\mathrm{\φ}-{\mathrm{\Ω}}^{2}rcos\mathrm{\φ}\cos \mathrm{\γ}sin\mathrm{\φ}cos\mathrm{\ψ})---\left(12\right)$

$\begin{array}{c}V\stackrel{\·}{\mathrm{\γ}}=Lcos\mathrm{\σ}+(V^2-\frac{1}{r})\left(\frac{cos\mathrm{\γ}}{r}\right)+2\mathrm{\Ω}Vcos\mathrm{\φ}\sin \mathrm{\ψ}\\ +{\mathrm{\Ω}}^{2}r\cos \mathrm{\φ}\cos \mathrm{\γ}\cos \mathrm{\φ}+{\mathrm{\Ω}}^{2}r\cos \mathrm{\φ}\sin \mathrm{\γ}\cos \mathrm{\ψ}\sin \mathrm{\φ}\end{array}---\left(13\right)$

$\begin{array}{c}V\stackrel{\·}{\mathrm{\ψ}}=\frac{L\sin \mathrm{\σ}}{\cos \mathrm{\γ}}+\frac{V^2}{r}cos\mathrm{\γ}\sin \mathrm{\ψ}\tan \mathrm{\φ}\\ -2\mathrm{\Ω}V\tan \mathrm{\γ}\cos \mathrm{\ψ}\cos \mathrm{\φ}-2\mathrm{\Ω}V\sin \mathrm{\φ}+\frac{{\mathrm{\Ω}}^{2}r}{\cos \mathrm{\γ}}\sin \mathrm{\γ}\sin \mathrm{\φ}\cos \mathrm{\φ}\end{array}---\left(14\right)$

Wherein, micro component is time ��, namelyR is the earth center distance to aircraft, and �� is earth rotation speed, and scale factor is�� and �� respectively terrestrial longitude and latitude, �� is flight path angle, and �� is course angle (direct north is just clockwise), and �� is angle of heel, i.e. controlled quentity controlled variable,

Above-mentioned steps 4 is to described fitness function global optimization, and described global optimization method is particle swarm optimization algorithm, and concrete optimization step is as follows:

Step 4.1, initialization population, set population parameter, and give initial position and initial velocity at random for each particle;

Step 4.2, calculate the overload peak value that each particle is corresponding;

Step 4.3, determine as former generation k population each particle case history optimal location p_i(k), i=1,2 ..., the optimal location p that N and population experience up to now_g(k), wherein N is the population of population;

Step 4.4, the speed updating each particle and position;

Step 4.5, update the global optimum position of whole population;

p_g(k)=arg{min (f [p_g(k)])}(15)

Step 4.6, inspection end condition, if current evolution number of times reaches the maximum evolutionary generation preset or optimum results reaches to preset error, then optimizing terminates, output optimal solution and optimal value, otherwise will return (4.2) and proceed search;

The present invention compared with prior art has a characteristic that

(1) owing to employing prediction correction guidance and standard trajectory homing guidance combine and build integrated guidance strategy, gained track is made to meet each constraints in certain error precision, it is ensured that the feasibility of track;

(2) owing to adopting secondary to reenter angle of heel optimization, when not affecting landing precision, it is possible to conveniently realize unloading;

(3) owing to adopting particle cluster algorithm to carry out track optimizing, thus there is Fast Convergent and global optimizing characteristic, meet the accuracy of track optimizing, rapidity and feasibility.

Accompanying drawing explanation

Fig. 1 is the flow chart of embodiment provided by the invention;

Fig. 2 is the analogous diagram after embodiment track optimizing population provided by the invention initializes;

Fig. 3 is that embodiment provided by the invention is entered mark and optimized population and evolve the analogous diagram after 10 generations;

Fig. 4 is that embodiment track optimizing population provided by the invention is evolved the analogous diagram after 20 generations;

Fig. 5 is that embodiment track optimizing population provided by the invention is evolved the analogous diagram after 50 generations;

Fig. 6 is the convergence curve of embodiment track optimizing (unloading) provided by the invention.

Detailed description of the invention

Reach, for the present invention is expanded on further, technological means and effect that predetermined purpose is taked, below in conjunction with drawings and Examples, the specific embodiment of the present invention is described in further detail.

Aircraft adopts Apollo return capsule parameter, quality 5443kg, bottom reference area 12m², maximum angle of heel speed is 20deg/s, and maximum angle of heel acceleration is 10deg/s, and air mileage is 5000km, and reentry condition is voyage 5000km, height 120km, initial velocity 110km/s. Reentry point longitude and latitude (244.8 �� ,-41.1 ��), landing point longitude and latitude (242.1 ��, 34 ��).

With reference to Fig. 1, the present embodiment to implement step as follows:

Step 1, set up low lift-drag ratio aircraft and reenter the kinetic model of process;

The integrated guidance method design Guidance Law that step 2, employing prediction correction method of guidance and reference-trajectory guidance method combine:

According to the atmospheric density feature at differing heights layer, simultaneously take account of the precision to guidance and the requirement of calculated performance. Adopt a kind of integrated guidance method design Guidance Law predicting that correction method of guidance and reference-trajectory guidance method combine. Skip trajectory is divided into two stages, first reentry stage and secondary reentry stage. First reentry stage, highly about 120km, speed is about 11km/s. This stage reentry velocity is relatively big, and the unstability of air is relatively big simultaneously, and correction reentry guidance method is to guarantee the precision of this phase guidance therefore to adopt robustness to predict preferably. First re-entry phase includes again descending branch, ascent stage and Kepler's section. Angle of heel is planned to the function of range-to-go by this stage, and on horizontal and vertical, voyage is carried out decoupling, makes the range-to-go orthodrome distance equal to current point to drop point of aircraft, and the differential equation of range-to-go is:

$\stackrel{\·}{s}=\frac{Vcos\mathrm{\γ}}{r}---\left(1\right)$

Wherein, r is the earth center distance to aircraft, and �� is flight path angle, and V is flight speed.

Terminal control condition:

��(t_f)=��_f, �� (t_f)=��_f, r (t_f)=r_f(2)

��₀For initially reentering angle of heel, ��_2thAngle of heel is reentered for secondary. Angle of heel Parametric optimization problem can be described as: finds a ��₀, the specific speed in make it in the end stage disclosure satisfy that the offset landings requirement arriving target. For guaranteeing the OK range of angle of heel, and make planning continuous, adopt angle of heel linearization technique

$\left|\mathrm{\σ}\right|={\mathrm{\σ}}_{2th}+({\mathrm{\σ}}_0-{\mathrm{\σ}}_{2th})\frac{s-s_{2th}}{s_0-s_{2th}}---\left(3\right)$

Wherein, S₀For initial residual voyage, S_2thRange-to-go when reentering for secondary, is approximately 2000km, ��_2thTaking 70 ��, the methods such as therefore solving of �� can be converted into one-parameter and look for one's roots problem, available secant method solve, and the symbol of �� adopts horizontal logic.

Secondary re-entry phase is highly about 80km being 0.05g from overload. This stage characteristic be speed significantly lower than the first stage, less in the fluctuation of this stage atmospheric density. Therefore this stage adopts standard trajectory tracking, can reduce the aircraft requirement to calculated performance.

Step 3, definition fitness function:

The aircraft considered belongs to typical campanula halleri Halleri, and in flight course, aircraft normal g-load and axial acceleration are all likely to occur situation about surpassing the expectation, and therefore adopts the form of total overload:

$n_a=\sqrt{L^2+D^2}---\left(4\right)$

Wherein, L and D respectively rises/drag acceleration, defines as follows:

D=�� (V_sV)²S_refC_D/(2m)(5)

L=�� (V_sV)²S_refC_L/(2m)(6)

Wherein, S_refFor aircraft with reference to surface area, C windward_DAnd C_LRespectively resistance and lift coefficient, m is vehicle mass, and �� is atmospheric density, and the scale factor of speed V isR₀For earth radius, g₀=9.81m/s.

Formula (5) and (6) are substituted into (4) can obtain

$n_a=\mathrm{\ρ}{\left(V_{s}V\right)}^2{S}_{ref}\sqrt{C_L^2+C_D^2}/\left(2m\right)\∝{\mathrm{\ρV}}^2---\left(7\right)$

Having significant change in first re-entry phase and secondary re-entry phase aircraft speed, first re-entry phase speed is relatively big, but atmospheric density is relatively small; And secondary re-entry phase speed reduces to some extent, but atmospheric density is relatively large, and therefore, in ablated configuration process, overload is it is possible that two minor peaks, defines following fitness function:

Fitnessfunction=max [n_a(��_2th)](8)

Step 4, to described fitness function global optimization, by optimize ask for total overload values minimum time angle of heel, and this angle of heel is initially reentered angle of heel as the secondary of practical flight, wherein secondary reenters initial angle of heel ��₀In (0 ��, 90 ��) interval value.

The optimization of distribution and the angle of heel of overload has much relations, unsuitable angle of heel to there is a possibility that aircraft bears unnecessary overload, brings the selection of angle of heel that security threat, secondary reenter to be transship the key optimized in guidance to occupant. Experimental analysis is it can be seen that secondary reenters initial angle of heel ��₀Time too low, it is possible to can cause that aircraft in the end stage voyage regulating power is not enough, destroy aircraft lands precision.

Step 5, according to optimum results export corresponding reentry trajectory.

Further, it is dimensionless three-degree-of-freedom motion equation that the low lift-drag ratio aircraft that described step 1 is set up reenters the kinetic model of process, specific as follows:

$\stackrel{\·}{r}=Vsin\mathrm{\γ}---\left(9\right)$

$\stackrel{\·}{\mathrm{\θ}}=\frac{Vcos\mathrm{\γ}sin\mathrm{\ψ}}{rcos\mathrm{\φ}}---\left(10\right)$

$\stackrel{\·}{\mathrm{\φ}}=\frac{V\cos \mathrm{\γ}cos\mathrm{\ψ}}{r}---\left(11\right)$

$\stackrel{\·}{V}=-D-\left(\frac{sin\mathrm{\γ}}{r^2}\right)+{\mathrm{\Ω}}^{2}rcos\mathrm{\φ}\sin \mathrm{\γ}cos\mathrm{\φ}-{\mathrm{\Ω}}^{2}rcos\mathrm{\φ}\cos \mathrm{\γ}sin\mathrm{\φ}cos\mathrm{\ψ})---\left(12\right)$

$\begin{array}{c}V\stackrel{\·}{\mathrm{\γ}}=Lcos\mathrm{\σ}+(V^2-\frac{1}{r})\left(\frac{cos\mathrm{\γ}}{r}\right)+2\mathrm{\Ω}Vcos\mathrm{\φ}\sin \mathrm{\ψ}\\ +{\mathrm{\Ω}}^{2}r\cos \mathrm{\φ}\cos \mathrm{\γ}\cos \mathrm{\φ}+{\mathrm{\Ω}}^{2}r\cos \mathrm{\φ}\sin \mathrm{\γ}\cos \mathrm{\ψ}\sin \mathrm{\φ}\end{array}---\left(13\right)$

$\begin{array}{c}V\stackrel{\·}{\mathrm{\ψ}}=\frac{Lcos\mathrm{\σ}}{\cos \mathrm{\γ}}+\frac{V^2}{r}cos\mathrm{\γ}\sin \mathrm{\ψ}\tan \mathrm{\φ}\\ -2\mathrm{\Ω}V\tan \mathrm{\γ}\cos \mathrm{\ψ}\cos \mathrm{\φ}-2\mathrm{\Ω}V\sin \mathrm{\φ}+\frac{{\mathrm{\Ω}}^{2}r}{\cos \mathrm{\γ}}\sin \mathrm{\γ}\sin \mathrm{\φ}\cos \mathrm{\φ}\end{array}---\left(14\right)$

Wherein, micro component is time ��, namelyR is the earth center distance to aircraft, and �� is earth rotation speed, and scale factor is�� and �� respectively terrestrial longitude and latitude, �� is flight path angle, and �� is course angle (direct north is just clockwise), and �� is angle of heel, i.e. controlled quentity controlled variable,

Further, the global optimization method described in step 4 is particle swarm optimization algorithm, and concrete optimization step is as follows:

Step 4.1, initialization population, set population parameter, and give initial position and initial velocity at random for each particle;

Step 4.2, calculate the overload peak value that each particle is corresponding;

Step 4.3, determine as former generation k population each particle case history optimal location p_i(k), i=1,2 ..., the optimal location p that N and population experience up to now_g(k), wherein N is the population of population;

Step 4.4, the speed updating each particle and position;

Step 4.5, update the global optimum position of whole population;

p_g(k)=arg{min (f [p_g(k)])}(15)

Step 4.6, inspection end condition, if current evolution number of times reaches the maximum evolutionary generation preset or optimum results reaches to preset error, then optimizing terminates, output optimal solution and optimal value, otherwise will return (4.2) and proceed search;

The track optimizing analogous diagram of Fig. 2��Fig. 5 the present embodiment. Wherein Fig. 2 show the analogous diagram of track optimizing iteration 1 time, and Fig. 3 show the analogous diagram of track optimizing iteration 5 times, and Fig. 4 show the analogous diagram of track optimizing iteration 10 times, and wherein heavy line represents the optimal particle in population in the present age; Fig. 5 show the aircraft reentry trajectory after track optimizing. From Fig. 2��Fig. 4 it can be seen that owing to adopting particle cluster algorithm to carry out global optimization, optimizing track can effectively unload.

Fig. 6 show the present invention and carries out the convergence curve of track optimizing, from fig. 6, it can be seen that due to the fact that employing particle group optimizing method, can rapidly converge to global optimum's track after 10 generations of evolving.

Above content is in conjunction with concrete preferred implementation further description made for the present invention, it is impossible to assert that specific embodiment of the invention is confined to these explanations. For general technical staff of the technical field of the invention, without departing from the inventive concept of the premise, it is also possible to make some simple deduction or replace, protection scope of the present invention all should be considered as belonging to.

Claims (3)

1. one kind low lift-drag ratio recoverable capsule integrated guidance discharging method, it is characterised in that comprise the steps:

Step 1, set up low lift-drag ratio aircraft and reenter the kinetic model of process;

The integrated guidance method design Guidance Law that step 2, employing prediction correction method of guidance and reference-trajectory guidance method combine, step is as follows:

Step 2.1, skip trajectory is divided into two stages, first reentry stage and secondary reentry stage;

Step 2.2, described first reentry stage height are about 120km, and speed is about 11km/s, and angle of heel is planned to the function of range-to-go by this stage:

$\left|\mathrm{\σ}\right|={\mathrm{\σ}}_{2th}+({\mathrm{\σ}}_0-{\mathrm{\σ}}_{2th})\frac{S-S_{2th}}{S_0-S_{2th}}$

Wherein, ��₀For initially reentering angle of heel, ��_2thAngle of heel, S is reentered for secondary₀For initial residual voyage, S_2thRange-to-go when reentering for secondary, is approximately 2000km, ��_2thBeing 70 ��, the symbol of �� adopts horizontal logic;

Step 2.3, described secondary re-entry phase are from overload for, 0.05g, being highly about 80km, and this stage adopts standard trajectory tracking;

Step 3, definition fitness function, described fitness function is as follows:

Fitnessfunction=max [n_a(��_2th)]

Wherein always transship $n_a=\mathrm{\ρ}{\left(V_{s}V\right)}^2{S}_{ref}\sqrt{C_L^2+C_D^2}/\left(2m\right)\∝{\mathrm{\ρV}}^2,$ The scale factor of speed V $V_s=\sqrt{R_0{g}_0},$ R₀For earth radius, g₀=9.81m/s, S_refFor aircraft with reference to surface area, C windward_DAnd C_LRespectively resistance and lift coefficient, m is vehicle mass, and �� is atmospheric density, initially reenters angle of heel ��₀In (0 ��, 90 ��) interval value;

Step 4, to described fitness function global optimization, take total overload values minimum time angle of heel initially reenter angle of heel as the secondary of practical flight;

Step 5, according to optimum results export corresponding reentry trajectory.

2. one according to claim 1 low lift-drag ratio recoverable capsule integrated guidance discharging method, it is characterised in that the kinetic model described in step 1 is dimensionless three-degree-of-freedom motion equation.

3. one according to claim 1 low lift-drag ratio recoverable capsule integrated guidance discharging method, it is characterised in that the global optimization method described in step 4 is particle group optimizing, and optimization step is as follows:

Step 4.1, initialization population, set population parameter, and give initial position and initial velocity at random for each particle;

Step 4.2, calculate the overload peak value that each particle is corresponding;

Step 4.3, determine as former generation k population each particle case history optimal location p_i(k), i=1,2 ..., the optimal location p that N and population experience up to now_g(k), wherein N is the population of population;

Step 4.4, the speed updating each particle and position;

Step 4.5, update the global optimum position of whole population;

Step 4.6, inspection end condition, if current evolution number of times reaches the maximum evolutionary generation preset or optimum results reaches to preset error, then optimizing terminates, output optimal solution and optimal value, otherwise will return (4.2) and proceed search.